tbuckley/cabot-search huggingface dataset:
Abstract IA05: Nodal and systemic Immune effects of radiation in HNSCC
Authors: Laurel B. Darragh, Jacob Gadwa, Keara Boss, Sana D. Karam
Journal: Clinical Cancer Research (2023)

Abstract When combined with immunotherapy, HPV-unrelated HNSCC has a high incidence of local and regional recurrence. Since nodal metastasis remains a common pattern of spread for HNSCC, elective nodal irradiation (ENI) is commonly employed to eradicate potential microscopic disease in non-involved lymph nodes. Given our developing understanding that (1) immune cells are highly radio-sensitive, and (2) that anti-tumor T cell priming, and expansion, occur in the draining lymph nodes (DLNs), we tested whether RT directed at gross tumor only could increase the effectiveness of immunotherapies. Using preclinical models and samples from canine and human trials, we tested the effects of RT with or without ENI. Immune cell differences in the tumor tissue, DLNs, and blood were characterized with flow cytometry. We found that tumor only irradiation decreased local and distant tumor growth and increased survival but increased regional recurrence. Sentinel lymph node resection or irradiation was effective at reducing regional metastasis. We show that the effectiveness of tumor only RT is likely mediated via induction of a systemic immune response dependent on antigen recognition by T cells in the DLNs. These data support the hypothesis that effective anti-tumor immunotherapy treatment requires a systemic, antigen-dependent immune response which is primed in the DLNs. Citation Format: Laurel B. Darragh, Jacob Gadwa, Keara Boss, Sana D. Karam. Nodal and systemic Immune effects of radiation in HNSCC [abstract]. In: Proceedings of the AACR-AHNS Head and Neck Cancer Conference: Innovating through Basic, Clinical, and Translational Research; 2023 Jul 7-8; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2023;29(18_Suppl):Abstract nr IA05.
Machine learning for individualized prediction of hepatocellular carcinoma development after the eradication of hepatitis C virus with antivirals
Authors: Tatsuya Minami, Masaya Sato, Hidenori Toyoda, Satoshi Yasuda, Tomoharu Yamada, Takuma Nakatsuka, Kenichiro Enooku, Hayato Nakagawa, Hidetaka Fujinaga, Masashi Izumiya, Yasuo Tanaka, Motoyuki Otsuka, Takamasa Ohki, Masahiro Arai, Yoshinari Asaoka, Atsushi Tanaka, Kiyomi Yasuda, Hideaki Miura, Itsuro Ogata, Toshiro Kamoshida, Kazuaki Inoue, Ryo Nakagomi, Masatoshi Akamatsu, Hiroshi Mitsui, Hajime Fujie, Keiji Ogura, Koji Uchino, Hideo Yoshida, Kazuyuki Hanajiri, Tomonori Wada, Kiyohiko Kurai, Hisato Maekawa, Yuji Kondo, Shuntaro Obi, Takuma Teratani, Naohiko Masaki, Kayo Nagashima, Takashi Ishikawa, Naoya Kato, Hiroshi Yotsuyanagi, Kyoji Moriya, Takashi Kumada, Mitsuhiro Fujishiro, Kazuhiko Koike, Ryosuke Tateishi
Journal: Journal of Hepatology (2023)
Retraction notice to “Aldehyde dedydrogenase-2 plays a beneficial role in ameliorating chronic alcohol-induced hepatic steatosis and inflammation through regulation of autophagy” [J Hepatol 62 (3) (2015) 647–656]
Authors: Rui Guo, Xihui Xu, Sara A. Babcock, Yingmei Zhang, Jun Ren
Journal: Journal of Hepatology (2023)
JHEP at a glance (Month 20XX)
Authors: Manuel Romero-Gómez, Eric Lawitz, R Ravi Shankar, Raymond Lam, Keith Kaufman, Samuel Engel, Fanny Lalloyer, Denis Mogilenko, Ann Verrijken, Jean-François Goossens, Sven Francque, Bart Staels, Laure Elkrief, Nathalie Ganne-Carrié, Hana Manceau, Thierry Poynard, Sylvie Chevret, Pierre-Emmanuel Rautou, Ed Gane, Young-Suk Lim, Jae Kim, Christy Hebner, Phillip Pang, Man-Fung Yuen
Journal: Journal of Hepatology (2023)
Neural cell membrane-coated DNA nanogels as a potential target-specific drug delivery tool for the central nervous system
Authors: Po Hen Lin, Chongquan Huang, Yuwei Hu, Vaibavi Srirangam Ramanujam, Ee-Soo Lee, Ruby Singh, Ulla Milbreta, Christine Cheung, Jackie Y. Ying, Sing Yian Chew
Journal: Biomaterials (2023)
Closed loop BCI system for Cybathlon 2020
Authors: Csaba Köllőd, András Adolf, Gergely Márton, Moutz Wahdow, Ward Fadel, István Ulbert
Journal: Brain-Computer Interfaces (2023)

We developed a Brain-Computer Interface (BCI) System for the BCI discipline of Cybathlon 2020 competition, where participants with tetraplegia (pilots) control a computer game with mental commands. To extract features from one-second-long electroencephalographic (EEG) signals, we calculated the absolute of the Fast-Fourier Transformation amplitude (FFTabs) and introduced two methods: Feature Average and Feature Range. The former calculates the average of the FFTabs for a specific frequency band, while the later generates multiple Feature Averages for non-overlapping 2 Hz wide frequency bins. The resulting features were fed to a Support Vector Machine classifier and tested on the PhysioNet database and our dataset containing 16 offline experiments recorded with the help of 2 pilots. 27 gameplay trials (out of 59) with our pilots reached the 240-second qualification time limit, which demonstrates the usability of our system in real-time circumstances. We critically compared the Feature Average of canonical frequency bands (alpha, beta, gamma, and theta) with our suggested range30 and range40 methods. On the PhysioNet dataset, the range40 method combined with an ensemble SVM classifier significantly reached the highest accuracy level (0.4607), with a 4-class classification; moreover, it outperformed the state-of-the-art EEGNet.
Role of preoperative in-hospital delay on appendiceal perforation while awaiting appendicectomy (PERFECT): a Nordic, pragmatic, open-label, multicentre, non-inferiority, randomised controlled trial
Authors: Karoliina Jalava, Ville Sallinen, Hanna Lampela, Hanna Malmi, Ingeborg Steinholt, Knut Magne Augestad, Ari Leppäniemi, Panu Mentula
Journal: The Lancet (2023)
Evaluating the usefulness of the Atopic Dermatitis Control Tool for assessing disease control in individuals with atopic dermatitis in Japan
Authors: Takeshi Nakahara, Hiroyuki Fujita, Yuki Tajima, Kazuhiko Arima
Journal: British Journal of Dermatology (2023)

An online questionnaire assessed atopic dermatitis (AD)-related patient-reported outcome measures [including the Atopic Dermatitis Control Tool (ADCT)] in 5546 patients with AD. Spearman’s rank correlation coefficients showed that total ADCT scores had strong correlations with established AD assessment tools (including the DLQI, POEM and WI-NRS). ADCT subitem scores also had moderate correlations with the other AD assessment tools, except for Q4 (sleep) with the Global Questions assessment tool. This demonstrates that ADCT scores can effectively characterize multidimensional AD disease burden.
Genetic Origins and Adaptive Evolution of the Deng People on the Tibetan Plateau
Authors: Xueling Ge, Yan Lu, Shuanghui Chen, Yang Gao, Lifeng Ma, Lijun Liu, Jiaojiao Liu, Xixian Ma, Longli Kang, Shuhua Xu
Journal: Molecular Biology and Evolution (2023)

The Tibetan Plateau is populated by diverse ethnic groups, but most of them are underrepresented in genomics studies compared with the Tibetans (TIB). Here, to gain further insight into the genetic diversity and evolutionary history of the people living in the Tibetan Plateau, we sequenced 54 whole genomes of the Deng people with high coverage (30-60×) and analyzed the data together with that of TIB and Sherpas, as well as 968 ancient Asian genomes and available archaic and modern human data. We identified 17.74 million novel single-nucleotide variants from the newly sequenced genomes, although the Deng people showed reduced genomic diversity and a relatively small effective population size. Compared with the other Tibetan highlander groups which are highly admixed, the Deng people are dominated by a sole ancestry that could be traced to some ancient northern East Asian populations. The divergence between Deng and Tibetan people (∼4,700-7,200 years) was more recent than that between highlanders and the Han Chinese (Deng-HAN, ∼9,000-14,000 years; TIB-HAN, 7,200-10,000 years). Adaptive genetic variants (AGVs) identified in the Deng are only partially shared with those previously reported in the TIB like HLA-DQB1, whereas others like KLHL12 were not reported in TIB. In contrast, the top candidate genes harboring AGVs as previously identified in TIB, like EPAS1 and EGLN1, do not show strong positive selection signals in Deng. Interestingly, Deng also showed a different archaic introgression scenario from that observed in the TIB. Our results suggest that convergent adaptation might be prevalent on the Tibetan Plateau.
Cardiomyocyte and endothelial cells play distinct roles in the tumour necrosis factor (TNF)-dependent atrial responses and increased atrial fibrillation vulnerability induced by endurance exercise training in mice
Authors: Robert Lakin, Nazari Polidovitch, Sibao Yang, Mihir Parikh, Xueyan Liu, Ryan Debi, Xiaodong Gao, Wenliang Chen, Camilo Guzman, Simona Yakobov, Farzad Izaddoustdar, Marianne Wauchop, Qian Lei, Weimin Xu, Sergei A Nedospasov, Vincent M Christoffels, Peter H Backx
Journal: Cardiovascular Research (2023)

Abstract Aims Endurance exercise is associated with an increased risk of atrial fibrillation (AF). We previously established that adverse atrial remodelling and AF susceptibility induced by intense exercise in mice require the mechanosensitive and pro-inflammatory cytokine tumour necrosis factor (TNF). The cellular and mechanistic basis for these TNF-mediated effects is unknown. Methods and results We studied the impact of Tnf excision, in either atrial cardiomyocytes or endothelial cells (using Cre-recombinase expression controlled by Nppa or Tie2 promoters, respectively), on the cardiac responses to six weeks of intense swim exercise training. TNF ablation, in either cell type, had no impact on the changes in heart rate, autonomic tone, or left ventricular structure and function induced by exercise training. Tnf excision in atrial cardiomyocytes did, however, prevent atrial hypertrophy, fibrosis, and macrophage infiltration as well as conduction slowing and increased AF susceptibility arising from exercise training. In contrast, endothelial-specific excision only reduced the training-induced atrial hypertrophy. Consistent with these cell-specific effects of Tnf excision, inducing TNF loss from atrial cardiomyocytes prevented activation of p38MAPKinase, a strain-dependent downstream mediator of TNF signalling, without affecting the atrial stretch as assessed by atrial pressures induced by exercise. Despite TNF’s established role in innate immune responses and inflammation, neither acute nor chronic exercise training caused measurable NLRP3 inflammasome activation. Conclusions Our findings demonstrate that adverse atrial remodelling and AF vulnerability induced by intense exercise require TNF in atrial cardiomyocytes whereas the impact of endothelial-derived TNF is limited to hypertrophy modulation. The implications of the cell autonomous effects of TNF and crosstalk between cells in the atria are discussed.
Surface modification strategies in translocating nano-vesicles across different barriers and the role of bio-vesicles in improving anticancer therapy
Authors: Pratiksha Tiwari, Krishna Yadav, Ravi Prakash Shukla, Shalini Gautam, Disha Marwaha, Madhu Sharma, Prabhat Ranjan Mishra
Journal: Journal of Controlled Release (2023)
Monoamines' role in islet cell function and type 2 diabetes risk
Authors: Fiona Louise Roberts, Luis Rodrigo Cataldo, Malin Fex
Journal: Trends in Molecular Medicine (2023)

The two monoamines serotonin and melatonin have recently been highlighted as potent regulators of islet hormone secretion and overall glucose homeostasis in the body. In fact, dysregulated signaling of both amines are implicated in β-cell dysfunction and development of type 2 diabetes mellitus (T2DM). Serotonin is a key player in β-cell physiology and plays a role in expansion of β-cell mass. Melatonin regulates circadian rhythm and nutrient metabolism and reduces insulin release in human and rodent islets in vitro. Herein, we focus on the role of serotonin and melatonin in islet physiology and the pathophysiology of T2DM. This includes effects on hormone secretion, receptor expression, genetic variants influencing β-cell function, melatonin treatment, and compounds that alter serotonin availability and signaling.
SRRM4-mediated REST to REST4 dysregulation promotes tumor growth and neural adaptation in breast cancer leading to brain metastasis
Authors: Krutika Deshpande, Vahan Martirosian, Brooke N Nakamura, Diganta Das, Mukund Iyer, Max Reed, Ling Shao, Daniella Bamshad, Noel J Buckley, Josh Neman
Journal: Neuro-Oncology (2023)

Abstract Background Effective control of brain metastasis remains an urgent clinical need due a limited understanding of the mechanisms driving it. Although the gain of neuro-adaptive attributes in breast-to-brain metastases (BBMs) has been described, the mechanisms that govern this neural acclimation and the resulting brain metastasis competency are poorly understood. Herein, we define the role of neural-specific splicing factor Serine/Arginine Repetitive Matrix Protein 4 (SRRM4) in regulating microenvironmental adaptation and brain metastasis colonization in breast cancer cells. Methods Utilizing pure neuronal cultures and brain-naive and patient-derived BM tumor cells, along with in vivo tumor modeling, we surveyed the early induction of mediators of neural acclimation in tumor cells. Results When SRRM4 is overexpressed in systemic breast cancer cells, there is enhanced BBM leading to poorer overall survival in vivo. Concomitantly, SRRM4 knockdown expression does not provide any advantage in central nervous system metastasis. In addition, reducing SRRM4 expression in breast cancer cells slows down proliferation and increases resistance to chemotherapy. Conversely, when SRRM4/REST4 levels are elevated, tumor cell growth is maintained even in nutrient-deprived conditions. In neuronal coculture, decreasing SRRM4 expression in breast cancer cells impairs their ability to adapt to the brain microenvironment, while increasing SRRM4/RE-1 Silencing Transcription Factor (REST4) levels leads to greater expression of neurotransmitter and synaptic signaling mediators and a significant colonization advantage. Conclusions Collectively, our findings identify SRRM4 as a regulator of brain metastasis colonization, and a potential therapeutic target in breast cancer.
The emerging potential of siRNA nanotherapeutics in treatment of arthritis
Authors: Anjali Kumari, Amanpreet Kaur, Geeta Aggarwal
Journal: Asian Journal of Pharmaceutical Sciences (2023)

RNA interference (RNAi) using small interfering RNA (siRNA) has shown potential as a therapeutic option for the treatment of arthritis by silencing specific genes. However, siRNA delivery faces several challenges, including stability, targeting, off-target effects, endosomal escape, immune response activation, intravascular degradation, and renal clearance. A variety of nanotherapeutics like lipidic nanoparticles, liposomes, polymeric nanoparticles, and solid lipid nanoparticles have been developed to improve siRNA cellular uptake, protect it from degradation, and enhance its therapeutic efficacy. Researchers are also investigating chemical modifications and bioconjugation to reduce its immunogenicity. This review discusses the potential of siRNA nanotherapeutics as a therapeutic option for various immune-mediated diseases, including rheumatoid arthritis, osteoarthritis, etc. siRNA nanotherapeutics have shown an upsurge of interest and the future looks promising for such interdisciplinary approach-based modalities that combine the principles of molecular biology, nanotechnology, and formulation sciences.
Latent Transformer Models for out-of-distribution detection
Authors: Mark S. Graham, Petru-Daniel Tudosiu, Paul Wright, Walter Hugo Lopez Pinaya, Petteri Teikari, Ashay Patel, Jean-Marie U-King-Im, Yee H. Mah, James T. Teo, Hans Rolf Jäger, David Werring, Geraint Rees, Parashkev Nachev, Sebastien Ourselin, M. Jorge Cardoso
Journal: Medical Image Analysis (2023)

Any clinically-deployed image-processing pipeline must be robust to the full range of inputs it may be presented with. One popular approach to this challenge is to develop predictive models that can provide a measure of their uncertainty. Another approach is to use generative modelling to quantify the likelihood of inputs. Inputs with a low enough likelihood are deemed to be out-of-distribution and are not presented to the downstream predictive model. In this work, we evaluate several approaches to segmentation with uncertainty for the task of segmenting bleeds in 3D CT of the head. We show that these models can fail catastrophically when operating in the far out-of-distribution domain, often providing predictions that are both highly confident and wrong. We propose to instead perform out-of-distribution detection using the Latent Transformer Model: a VQ-GAN is used to provide a highly compressed latent representation of the input volume, and a transformer is then used to estimate the likelihood of this compressed representation of the input. We demonstrate this approach can identify images that are both far- and near- out-of-distribution, as well as provide spatial maps that highlight the regions considered to be out-of-distribution. Furthermore, we find a strong relationship between an image's likelihood and the quality of a model's segmentation on it, demonstrating that this approach is viable for filtering out unsuitable images.
Cyclosporine vs. tacrolimus after liver transplantation for primary sclerosing cholangitis – a propensity score-matched intention-to-treat analysis
Authors: Fredrik Åberg, Ville Sallinen, Samuli Tuominen, René Adam, Vincent Karam, Darius Mirza, Michael A. Heneghan, Pål-Dag Line, William Bennet, Bo-Göran Ericzon, Michal Grat, Peter Lodge, Allan Rasmussen, Moritz Schmelzle, Douglas Thorburn, Constantino Fondevila, Ilkka Helanterä, Arno Nordin
Journal: Journal of Hepatology (2023)

There is controversy regarding the optimal calcineurin inhibitor type after liver transplant(ation) (LT) for primary sclerosing cholangitis (PSC). We compared tacrolimus with cyclosporine in a propensity score-matched intention-to-treat analysis based on registries representing nearly all LTs in Europe and the US.
INTEGRATIVE ANALYSIS OF DIFFERENTIALLY REGULATED PROTEINS IN MENINGIOMA
Authors: Maryam Shah, Matthew Banton, Claire Adams, Leandro De Assis, Vikram Sharma, Oliver Hanemann
Journal: Neuro-Oncology (2023)

Abstract AIMS Meningiomas are common primary intracranial tumours that arise from meninges. loss of chromosome 22q is common genetic event observed in meningiomas. About 50% of meningiomas harbour mutations in NF2 gene that resides on chromosome 22. Moreover, frequent mutations have been observed in AKT1, KLF4, TRAF7, and SMO genes. Meningiomas are divided into different genomic subgroups that express unique proteomic profiles. This study aims to investigate genomic background of meningioma and to determine the impact of mutations on underlying protein expression to identify druggable targets. METHOD Total 96 meningioma samples were sequenced using Illumina TruSight Oncology 500 panel. The raw sequence data was analyzed using TSO500 App. The variant data was annotated using Cancer Genome Interpreter and ANNOVAR. Clinical enrichment analysis was performed to investigate common pathways. Genomic data was correlated with LC-MS based proteomic data to determine variants effect on downstream processes. RESULTS Results showed an average of 1083 total and 7 driver mutations per sample. NF2 gene was found among highly mutated genes in tumour samples. Almost all NF2 mutations were frameshift, splice site and nonsense mutations, previously reported to be associated with high rate of multiple and recurring meningiomas. Additionally, driver mutations were identified in known meningioma genes including AKT1, KLF4, and TRAF7 along with previously unpublished mutations in ERBB2, MET, ARID5B, etc. The results correlate with tumour location, grade, and histopathological subtype. CONCLUSIONS The study identified common as well as unique driver mutations in meningioma samples. After functional validation, novel driver mutations could further enhance personalized treatment for meningioma patients.
PREDICTING GLIOBLASTOMA GENE EXPRESSION THERAPY RESPONSE WITH MACHINE LEARNING
Authors: Morgan Thomas, Stelios Theophanous, Isabelle Whittle, Martina Finetti, Steven Pollock, Nazia Ahmed, Georgette Tanner, Aruna Chakrabarty, Azzam Ismail, Andrew Bulpitt, Lucy Stead
Journal: Neuro-Oncology (2023)

Abstract AIMS The rapid recurrence of therapy-resistant glioblastoma leaves patients with a dismal 2-year survival rate of just 16%, highlighting the need to develop treatments that combat or prevent glioblastoma recurrence. Recently, glioblastoma patients have been stratified by their gene expression response to therapy. Specifically, genes with JARID2 binding sites in their promoter (JBS-genes) either become up- or down-regulated on progression from the primary to the recurrent tumour. Importantly, these two responses appear to employ different mechanisms of therapy resistance. Using gene expression data from primary tumours, we aim to predict the direction of JBS- gene dysregulation. Ultimately, this prediction could guide treatment decisions that prevent the acquisition of therapy resistance in glioblastoma. METHOD We used gene expression data from 84 primary glioblastoma tumours that had been labelled as either ‘Up’ or ‘Down’ responders based on the direction of JBS-gene dysregulation in matched recurrent tumours. We converted the RNA-sequencing data from the primary tumours to single-sample pathway scores, which were used to train several binary classification machine learning models. RESULTS A ridge regression model achieved an accuracy of 73.9% in predicting the direction of JBS-gene dysregulation in an independent set of 23 primary glioblastoma tumours. CONCLUSIONS Our classifier performs better than random chance demonstrating that gene expression data is informative and molecular features influence this gene expression response to therapy. However, there remains scope for improvement. This suggests further studies may benefit from integrating multiple data types such as genomics, epigenomics, tumour architecture, or clinical variables.
ROLE OF THE TRANSCRIPTIONAL ELONGATION FACTOR SPT6 AS A MODULATOR OF RAD52 IN GLIOBLASTOMA TUMOURS
Authors: Diana Aguilar-Morante, Petra Hamerlik
Journal: Neuro-Oncology (2023)

Abstract AIMS Glioblastoma (GBM) is the deadliest and most common primary brain tumour with median survival rates of less than two years. Inter- and intra-tumoral heterogeneity, cellular plasticity and de-regulated signalling pathways are plausible causes of resistance to existent therapies in GBM. As current therapies offer only limited survival benefits, the identification and validation of new approaches in glioblastoma management is of the highest importance METHOD • In silico analysis, RNA sequencing analysis after SPT6 depletion and analysis of R-loop formation after RAD52 depletion. • Patient-Derived Xenografts and primary human glioblastoma cells RESULTS Our recent findings show significantly higher RAD52 mRNA levels in malignant gliomas compared to normal brain, where its levels negatively correlate with GBM patient survival. Experimental data show that the inhibition of RAD52 by 6-Hydroxy-DL-Dopa (6OH-Dopa) impairs GBM cell survival due to increased replication- transcription collisions leading to the accumulation of DNA damage. Transcriptional elongation factor SPT6 has previously been named an essential gene in GBM. We find that loss of SPT6 decreases the expression of HR proteins BRCA1, RAD51 and RAD52. RAD52 binds to single-strand DNA (ssDNA), plays a crucial role in most HR events, and restarts collapsed replication forks in response to oncogene-induced replication stress. Further investigation into the role of RAD52 showed depletion of RAD52 results in an increase of R-loops increasing genomic instability and DNA damage. CONCLUSIONS Based on our findings, we hypothesize that SPT6 modulates RAD52, which acts as a sensor of R-loops and plays a crucial role in R-loops’ resolution.